通过14周协作设计，将抽象概念转化为可落地的医疗机器人原型。
Towards Considerate Embodied AI: Co-Designing Situated Multi-Site Healthcare Robots from Abstract Concepts to High-Fidelity Prototypes
- 跨学科团队从头脑风暴逐步构建高保真原型。
- 在三大医疗场景中验证了减少非必要工作负担的可行性。
- 提出4个维度8条指南，助力更贴心的智能机器人设计。
协同设计对将具身人工智能系统扎根于真实世界至关重要，尤其在医疗等高风险领域。尽管已有研究关注多学科合作、迭代原型与非技术人员支持，但很少将这些要素整合进持续的协同设计流程。以往工作多聚焦单一场景和低保真阶段，限制了成果的普适性，并模糊了参与者想法的演变过程。为此，我们组织了一支22人跨学科团队，开展为期14周的工作坊，探讨具身AI如何减轻急诊科、长期康复机构及睡眠障碍诊所中的非价值增值任务负担。结果表明，在教育支架支持下，从抽象构思到高保真原型的迭代过程，使参与者更理解现实权衡，提出更具部署可行性的方案。本文提出八项协同设计准则：情境敏感、响应社会动态、体察预期、面向实际部署。
原文摘要 · Abstract (English)
Co-design is essential for grounding embodied artificial intelligence (AI) systems in real-world contexts, especially high-stakes domains such as healthcare. While prior work has explored multidisciplinary collaboration, iterative prototyping, and support for non-technical participants, few have interwoven these into a sustained co-design process. Such efforts often target one context and low-fidelity stages, limiting the generalizability of findings and obscuring how participants' ideas evolve. To address these limitations, we conducted a 14-week workshop with a multidisciplinary team of 22 participants, centered around how embodied AI can reduce non-value-added task burdens in three healthcare settings: emergency departments, long-term rehabilitation facilities, and sleep disorder clinics. We found that the iterative progression from abstract brainstorming to high-fidelity prototypes, supported by educational scaffolds, enabled participants to understand real-world trade-offs and generate more deployable solutions. We propose eight guidelines for co-designing more considerate embodied AI: attuned to context, responsive to social dynamics, mindful of expectations, and grounded in deployment. Project Page: https://byc-sophie.github.io/Towards-Considerate-Embodied-AI/
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。